Data Engineer

Bachelor’s degree in Computer Science, Information Systems, Data Science, or related field. 2–4 years of experience in a data engineering role or similar environment. Hands-on experience building ETL/ELT jobs with AWS services (Glue, Lambda, Step Functions). Experience with orchestration tools like Airflow. Strong proficiency in Python and SQL. Experience working with Redshift Serverless, Aurora MySQL, Timestream, DynamoDB, or similar databases. Comfortable designing and managing S3-based data lakes with structured zone patterns. Experience implementing infrastructure-as-code using Terraform. Solid understanding of data modeling principles and performance optimization. Detail-oriented with a focus on quality, reliability, and maintainability. Excellent problem-solving abilities, organizational skills, and ability to manage multiple priorities. Strong communication skills, both written and verbal. Proven experience designing and implementing backend solutions in complex, scalable cloud environments. A proactive learner, eager to explore new technologies and methodologies. Comfortable in dynamic, collaborative environments, able to work independently and in teams.

Translate data models and product requirements into scalable data solutions. Develop and maintain ETL/ELT pipelines for data ingestion, processing, validation, and loading across AWS. Build and manage data workflows using AWS Glue, Lambda, and Step Functions. Work within structured S3 Raw, Curated, and Consumption zones. Participate in establishing data standards, naming conventions, and metadata practices. Incorporate AI-assisted development tools for data scrubbing, anomaly detection, and transformation. Use Terraform to define and manage data infrastructure. Troubleshoot data issues, performance bottlenecks, and pipeline failures. Implement data validation, monitoring, and quality checks. Load, maintain, and optimize datasets in Redshift Serverless, Aurora MySQL, DynamoDB, and Timestream. Write and optimize performant SQL queries, stored procedures, and database schemas. Monitor, manage, and optimize alerting systems (Sentry, Slack integrations). Create, manage, and improve infrastructure-as-code scripts and Terraform templates. Collaborate with Data Team to mature data practices and integration pipeline strategy. Collaborate with Product and Engineering Teams to implement system improvements. Participate in managing and coordinating production deployments and production support. Conduct code reviews, support Engineering Teams with backend best practices, and maintain documentation.